Cold-Pressed Walnut-Oil Adulteration with Edible Oils Detection Using Vis-NIR Spectroscopy

The aim of this study is to evaluate the usefulness of UV-Vis-NIR spectroscopy as a tool for detecting the adulteration of cold-pressed walnut oil and other edible oils (rapeseed, sunflower, and soybean oils) at varying percentages. The spectra were recorded between 200 and 1800 nm, but the analyses focused on 350–1650 nm due to high UV and NIR absorption. Color was determined in CIEL*a*b* coordinates to achieve the differences among the samples. The spectra were submitted to several pre-treatment (none, normalization, SNV, MSC, baseline/detrend, first/second derivative, and 1st-order smoothing) to improve the statistical model’s parameters. The differentiation of the samples was carried out using an unsupervised method (principal component analysis—PCA) and two supervised methods (linear discriminant analysis—LDA and partial least squares linear discriminant analysis—PLS-DA). Partial least squares regression (PLS-R) was used for predicting the degree of adulteration. Separation between the authentic and adulterated samples was visible in the PCA scores plot, primarily along the spectral regions of 420–500 nm (pigment-related absorption band) and 1150–1450 nm (lipid-associated band). PLS-DA was superior to DA for the discrimination of authentic/adulterated samples, with baseline spectra of 350–1650 nm yielding a 100% overall accuracy and near-perfect accuracy with MSC (98.48%). PLS-R was able to predict the adulteration level, depending on the pre-treatment applied.